Recently, the machine learning community uses the REINFORCE policy gradient algorithm to train non-differentiable hard attention models [1]}, [2]}, [3]}, [4]}, [5]}. Other recent works use EM-style learning procedure [6]}, wake-sleep algorithm [7]}, a voting based region selection [8]}, and spatial transformer [9]}, [10]}, [11]}. Among the recent methods, [2]}, [6]}, [7]} look at the low-resolution gist of an input at the beginning, and [3]}, [4]}, [11]}, [10]} consume the whole image to predict the locations to attend. In contrast, our model does not look at the entire image at low resolution or otherwise. Moreover, our model is fully differentiable.
